Method for Simultaneously Considering Customer Support Dates and Customer Request Dates

ABSTRACT

The invention disclosed here is a method for achieving simultaneous consideration of multiple customer demand dates within an advanced planning system. The invention provides a method of production planning that considers multiple due dates. The invention solves a production planning model based upon the second (commit) date to produce a first solution, sorts the demand records in order of importance, and then re-solves the production planning model based upon the first (request) date to produce a second solution. The re-solving process is performed on each demand item in the sorted order of importance. The invention optimizes between the first solution and the second solution. Before re-solving the production planning model, the invention changes the lower bound constraints on backorder variables. The re-solving process changes the required date for a single demand item, and this re-solving process is repeated for all demand items that have a first (request) date that is before a corresponding required date. The invention reports the optimal solution produced during the optimizing process. The system and method integrate the consideration of multiple demand dates with an advanced planning system for optimizing established planning objectives (e.g. customer service, short lead times, low inventory, and prioritized allocation of supply and capacity) to compute a feasible production plan for the division.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a Division of U.S. application Ser. No. 10/707,973filed Jan. 29, 2004, the complete disclosure of which, in its entirety,is herein incorporated by reference.

The present application is related to pending U.S. patent applicationSer. No. 10/707,978, filed concurrently herewith to Denton et al.,entitled “A METHOD FOR SUPPLY CHAIN COMPRESSION” having (IBM) Docket No.BUR920030197US1; U.S. patent application Ser. No. 10/707,974, filedconcurrently herewith to Denton et al., entitled “METHOD FOR PURCHASEORDER RESCHEDULING IN A LINEAR PROGRAM” having (IBM) Docket No.BUR92004009US1; U.S. patent application Ser. No. 10/707,977, filedconcurrently herewith to Denton et al., entitled “A METHOD FOR SUPPLYCHAIN DECOMPOSITION” having (IBM) Docket No. BUR920040007US1; U.S.patent application Ser. No. 10/707,976, filed concurrently herewith toDenton et al., entitled “A METHOD FOR OPTIMIZING FOUNDRY CAPACITY”having (IBM) Docket No. BUR920030195US1; U.S. patent application Ser.No. 10/707,972, filed concurrently herewith to Denton et al., entitled“METHOD FOR FAIR SHARING LIMITED RESOURCES BETWEEN MULTIPLE CUSTOMERS”having (IBM) Docket No. BUR920040010US1; U.S. patent application Ser.No. 10/707,979, filed concurrently herewith to Denton et al., entitled“A METHOD FOR CONSIDERING HIERARCHICAL PREEMPTIVE DEMAND PRIORITIES IN ASUPPLY CHAIN OPTIMIZATION MODEL” having (IBM) Docket No.BUR920030198US1; and U.S. patent application Ser. No. 10/708,119, filedconcurrently herewith to Orzell et al., entitled “METHOD FOR IDENTIFYINGPRODUCT ASSETS IN A SUPPLY CHAIN USED TO SATISFY MULTIPLE CUSTOMERDEMANDS” having Docket No. BUR820030346US1. The foregoing applicationsare assigned to the present assignee, and are all incorporated herein byreference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to computer implementable decision supportsystems for determining optimal supply chain plans based on multipledemand date considerations. General methodologies within this field ofstudy include advanced planning systems, optimization and heuristicbased algorithms, constraint based programming, and simulation.

2. Description of the Related Art

A fundamental problem faced in all manufacturing industries is theallocation of material and capacity assets to meet end customer demand.Production lead times necessitate the advance planning of productionstarts, interplant shipments, and material substitutions throughout thesupply chain so that these decisions are coordinated with the endcustomers” demand for any of a wide range of finished products(typically on the order of thousands in semiconductor manufacturing).Such advance planning depends upon the availability of finite resourceswhich include: finished goods inventory, work in process inventory (WIP)at various stages of the manufacturing system, and work-center capacity.Often, there are alternative possibilities for satisfying the demand.Products may be built at alternative locations and within a locationthere may be choices as to which materials or capacity to use to buildthe product. The product may be built directly or acquired throughmaterial substitution or purchase. When limited resources prevent thesatisfaction of all demands, decisions need to be made as to whichdemand to satisfy and how to satisfy it. This resource allocationproblem is often addressed through linear programming.

The below-referenced U.S. patents disclose embodiments that weresatisfactory for the purposes for which they were intended. Thedisclosures of both the below-referenced prior U.S. patents, in theirentireties, are hereby expressly incorporated by reference into thepresent invention for purposes including, but not limited to, indicatingthe background of the present invention and illustrating the state ofthe art: U.S. Pat. No. 5,971,585, “Best can do matching of assets withdemand in microelectronics manufacturing,” Oct. 26, 1999; U.S. Pat. No.5,943,484, “Advanced material requirements planning in microelectronicsmanufacturing,” Aug. 24, 1999; and Nemhauser, G. L. and Wolsey, L. A.,1999, Wiley, Integer and Combinatorial Optimization.

SUMMARY OF INVENTION

The invention comprises a method of production planning that considersmultiple demand dates. The invention performs production planning forboth the customer request date and the customer commit date. Theinvention also performs a binning operation to represent the multipledemand dates with demand priorities. A decision of whether the customerrequest date will be honored can be based on an associated priority thatmay depend in part upon a customer's willingness to pay premium prices.The customer commit date has a higher priority than the customer requestdate and the customer request date and the customer commit date areassociated with artificial part numbers that are based on the singlepart number. Thus, the invention provides a method for determining asupply chain plan that creates, from a single demand record, a pluralityof distinct demand records. Each of the distinct demand record has adifferent demand date. The invention performs core processing to createthe supply chain plan. This core processing considers all of thedistinct demand records. Also, the invention selects one of the distinctdemand records for supplying the single demand record, and thisselecting process can be based at least in part upon pricing. Forexample, the selecting process can provide different prices fordifferent demand dates.

In other words, the invention provides a method of production planningthat considers multiple due dates for providing the same resource to thesame demand item associated with an original part number. The multipledue dates can include (but are not limited to) for example, a first(request) date when the resource can be provided to the demand item, anda later second (commit) date when the resource must be provided to thedemand item. The invention creates, from the original part number, acommit-date part number associated with providing the resource to thedemand item by the second (commit) date and also creates, from theoriginal part number, a request-date part number associated withproviding the resource to the demand item by the first (request) date.

Then, the invention performs production planning for both thecommit-date part number and the request-date part number to determinewhen the resource can be provided to the demand item. After this, theinvention replaces the commit-date part number and the request-date partnumber with the original part number. The commit-date part number has ahigher priority than the request-date part number. The invention reportsto the demand item whether the resource will be supplied by the second(commit) date or the first (request) date. The invention uses duplicatebinning records to separately supply the commit-date part number and therequest-date part number.

The process of production planning simultaneously and separatelyprocesses objective functions and constraints for the commit-date partnumber from the request-date part number. The process of productionplanning simultaneously performs production planning for other resourcesand other demand items.

In another embodiment, the invention provides a method of productionplanning that considers multiple due dates. The invention solves aproduction planning model based upon the second (commit) date to producea first solution, sorts the demand records in order of importance, andthen re-solves the production planning model based upon the first(request) date to produce a second solution. The re-solving process isperformed on each demand item in the sorted order of importance. Theinvention optimizes between the first solution and the second solution.Before re-solving the production planning model, the invention changesthe lower bound constraints on backorder variables. The re-solvingprocess changes the required date for a single demand item, and thisre-solving process is repeated for all demand items that have a first(request) date that is before a corresponding required date. Theinvention reports the optimal solution produced during the optimizingprocess.

The present invention provides the capability to simultaneously considerboth request and commit dates for at least one customer demand. In orderto accomplish this, the invention introduces two “artificial” partnumbers for each part for which it is desirable to distinguish betweenrequest and commit dates. One artificial part will have low prioritydemand with a target date set to the request date. The other artificialpart will have normal priority demand with a target date set to thecommit date. Compared with conventional systems, by simultaneouslyconsidering both request and commit dates for a single demand, thisinvention provides a more efficient allocation of assets and resourcesgiven the objective to provide excellent customer service.

BRIEF DESCRIPTIONS OF DRAWINGS

FIG. 1: Overview of the structure of a typical linear programmingapplication.

FIG. 2: Illustration of demand splitting in which there is a customerrequest date and a customer commit date.

FIG. 3: Steps of the method for determining a supply chain plan based onconsideration of multiple demand dates.

FIG. 4: Steps of an alternate method for determining a supply chain planbased on consideration of multiple demand dates.

FIG. 5: Steps of the method for providing an earlier delivery date basedupon the customer paying a higher price for early delivery.

DETAILED DESCRIPTION

The present invention provides the capability to simultaneously considerboth request and commit dates for a single demand. This is done throughthe introduction of artificial part numbers where one artificial partsatisfies the requested demand and the other the committed demand. Tocontrast the present invention, a conventional production planninglinear program “LP” is shown below (such as that described in U.S. Pat.No. 5,971,585, which is incorporated herein by reference). This LP makesdecisions including: production starts, material substitutions, andshipments planned to customers, between manufacturing and distributionlocations, and from vendor suppliers. A LP is composed of an objectivefunction that defines a measure of the quality of a given solution, anda set of linear constraints. The types of equations used in productionplanning models are well know to those practiced in the art and include:

(1) Material Balance Constraints, which ensure conservation of materialflow through the network of stocking points comprising the supply chain.

(2) Capacity Constraints, which ensure that the capacity available formanufacturing activities is not exceeded.

(3) Backorder Conservation Constraints, which balance the quantity of agiven part backordered in a given planning period with the quantitybackordered in the previous planning period and the net of new demandand new shipments.

(4) Sourcing Constraints, which define target ranges (minimum andmaximum) of shipments that should be made from a particularmanufacturing or vendor location in the supply chain.

A conventional LP formulation is provided below in the form familiar tothose practiced in the art; i.e., definition of subscripts, definitionof objective function coefficients, definition of constants, definitionof decision variables, LP formulation or equations.

Definition of Subscripts

j—time period

m—material (part number)

a—plant location within the enterprise

n—material being substituted

z—group (which represents a family or collection of part numbers)

e—process (a method of purchasing or manufacturing a material at aplant)

v—receiving plant location

k—demand center (i.e., customer location) (Note: the set of customerlocations is mutually

exclusive from the set of plant locations)

q—demand class which indicates relative priority

w—resource capacity which could be a machine, labor hour, or otherconstraint

u—represents a consumer location which refers to an internal plant,external demand center, or to a generic indicator meaning any plant/ordemand center

Definition of Objective Function Coefficients

PRC_(jmae)—cost of releasing one piece of part m during period j atplant a using process e

SUBC_(jmna)—substitution cost per piece of part number n which is beingsubstituted by part number m during period j at plant a

TC_(jmav)—transportation cost per piece of part number m leaving plant aduring period j which are destined for plant v

INVC_(jma)—inventory cost of holding one piece of part number m at theend of period j at a particular plant a

DMAXC_(jzau)—cost per piece of exceeding the maximum amount of shipmentsof group z parts from plant a to consuming location(s) u during period j

DMINC_(jzau)—cost per piece of falling short of the minimum amount ofshipments specified for group z parts from plant a to consuminglocation(s) u during period j

BOC_(jmkq)—backorder cost of one piece of part m at the end of period jfor class q demand at customer location k

Definition of Constants

DEMAND_(jmkq)—demand requested during time period j for part number m atcustomer location k for demand class q

RECEIPT_(jma)—quantity of projected wip and purchase order receipts forpart number m expected to be received at plant a during time period j

CAPACITY_(jaw)—Capacity of resource w available at plant a during periodj to support production starts

CAPREQ_(jmaew)—Capacity of resource w required for part number m atplant a for process e during period j

QTYPER_(jmaen)—quantity of component m needed per part number n duringperiod j at plant a using process e

YIELD_(jmae)—output of part number m per piece released or started atplant a during time period j using process e

SUBQTY_(jmna)—quantity of part number m required to substitute for onepiece of part number n at plant a during time period j

MAXPCT_(jzau)—maximum percentage of total shipments of group z(collection of parts) leaving supplier a during period j to supportconsumption at consuming location(s) u

MINPCT_(jzau)—minimum percentage of total shipments of group z(collection of parts) leaving supplier a during period j to supportconsumption at consuming location(s) u

CT_(jmae)—Cycle time. The number of periods between the release andcompletion of part m jobs for releases made using process e at plant aduring time period j

TT_(mav)—transport time for part number m from plant a to plant v

Definition of LP Decision Variables

I_(jma)—Inventory at the end of period j for part number m at aparticular plant a

P_(jmae)—Production starts of part m during period j at plant a usingprocess e

L_(jmna)—Quantity of part number n which is being substituted by partnumber m during period j at plant a

T_(jmav)—Internal shipments of part number m leaving plant a duringperiod j which are destined for plant v

F_(jmakq)—Shipments of part number m leaving plant a during period j andsatisfying class q demand at external customer k

B_(jmkq)—Back orders of part m at the end of period j for class q demandat customer location k

H_(jzu)—Total shipments of group z (z is a “collection” of parts)leaving suppliers during period j to support consumption at consuminglocation(s) u

S_(jzau)—Amount by which total shipments of parts in z from plant a toconsuming location(s) u during period j exceeds the maximum amountspecified as desired in the sourcing rules

G_(jzau)—Amount by which total shipments of group z parts from plant ato consuming location(s) u during period j falls short of the minimumamount specified as desired in the sourcing rules

LP Equations or Formulation

The following minimizes the objective function subject to theconstraints shown below.

Objective Function:

Minimize:

${\sum\limits_{j}^{\;}\; {\sum\limits_{\mspace{11mu} m}^{\;}\; {\sum\limits_{a}^{\;}\; {\sum\limits_{e}^{\;}\; {{PRC}_{jmae}P_{jmae}}}}}} + {\sum\limits_{j}^{\;}\; {\sum\limits_{m}^{\;}\; {\sum\limits_{n}^{\;}\; {\sum\limits_{a}^{\;}\; {{SUBC}_{jmna}L_{jmna}}}}}} + {\sum\limits_{j}^{\;}\; {\sum\limits_{m}^{\;}\; {\sum\limits_{a}^{\;}\; {\sum\limits_{v}^{\;}\; {{TC}_{jmav}T_{jmav}}}}}} + {\sum\limits_{j}^{\;}\; {\sum\limits_{m}^{\;}\; {\sum\limits_{a}^{\;}\mspace{11mu} {{INVC}_{jma}I_{jma}}}}} + {\sum\limits_{j}^{\;}\; {\sum\limits_{z}^{\;}\; {\sum\limits_{a}^{\;}\; {\sum\limits_{u}^{\;}\; {{DMAXC}_{jzau}S_{jzau}}}}}} + {\sum\limits_{j}^{\;}\; {\sum\limits_{z}^{\;}\; {\sum\limits_{a}^{\;}\; {\sum\limits_{u}^{\;}\; {{DMINC}_{jzau}G_{jzau}}}}}} + {\sum\limits_{j}^{\;}\; {\sum\limits_{m}^{\;}\; {\sum\limits_{k}^{\;}\; {\sum\limits_{q}^{\;}\; {{BOC}_{jmkq}B_{jmkq}}}}}}$

Subject to:

Sourcing Constraints:

$H_{jzu} = {\sum\limits_{\underset{ɛ\; z}{m}}^{\;}\; {\sum\limits_{a}^{\;}\; \left( {T_{jmau} + {\sum\limits_{q}^{\;}\; F_{jmauq}}} \right)}}$${{\sum\limits_{\underset{ɛ\; z}{m}}^{\;}\; \left( {T_{jmau} + {\sum\limits_{q}^{\;}\; F_{jmauq}}} \right)} - S_{jzau}} \leq {{MAXPCT}_{jzau}H_{jzu}}$${{\sum\limits_{\underset{ɛ\; z}{m}}^{\;}\; \left( {T_{jmau} + {\sum\limits_{q}^{\;}\; F_{jmauq}}} \right)} + G_{jzau}} \geq {{MINPCT}_{jzau}H_{jzu}}$

Capacity Constraints:

${\sum\limits_{m}^{\;}\; {\sum\limits_{e}^{\;}\; {{CAPREQ}_{jmaew}P_{jmae}}}} \leq {CAPACITY}_{jaw}$

Backorder Constraints:

$B_{jmkq} = {B_{{({j - 1})}{mkq}} + {DEMAND}_{jmkq} - {\sum\limits_{a}^{\;}\; F_{jmakq}}}$

Material Balance Constraints:

$I_{jma} = {I_{{({j - 1})}{ma}} + {RECEIPT}_{jma} + {\sum\limits_{{xsi},{{{tx} + {CT}_{xmae}} = j}}^{\;}\; {\sum\limits_{e}^{\;}\; {{YIELD}_{xmae}*P_{xmae}}}} + {\sum\limits_{n}^{\;}\; L_{jmna}} + {\sum\limits_{{xs},{{{tx} + {TT}_{mav}} = j}}^{\;}\; {\sum\limits_{v}^{\;}\; T_{xmva}}} - {\sum\limits_{n}^{\;}{{SUBQTY}_{jmna}*L_{jmna}}} - {\sum\limits_{v}^{\;}T_{jmav}} - {\sum\limits_{k}^{\;}{\sum\limits_{q}^{\;}F_{jmakq}}} - {\sum\limits_{\underset{{is}\; a\; \underset{{of}\; n}{component}}{{nst},m}}^{\;}\; {\sum\limits_{e}^{\;}{{QTYPER}_{jmaen}P_{jnae}}}}}$

Non-Negativity Constraints:

all X_(i,j . . .) ≧0, where X is a generic decision variable and i, jetc. represent generic subscripts

The supply chain linear programming model shown above only allows forconsideration of a single customer demand date. Typically, a user willprovide demand as input based on the customer “commit” date, even thoughthis commit date may be later than a customer's original “request” date.The present invention allows for consideration of multiple dates, forexample, attempting to guarantee meeting a customer commit date while atthe same time attempting to achieve the customer's original requestdate, if possible.

Conventional advanced planning systems attempt to satisfy each demand ona given date. This date may be the commit date for a committed customerorder, a request date for a new order, or an expected date for aforecasted demand, as examples. However, manufacturers have encounteredsituations where it is desirable to consider multiple dates. By way ofexample, suppose that in September, a manufacturer commits to satisfyinga particular demand on March 31^(st) of the following year and that thisdate is later than the customer's original request date of March 1^(st)(perhaps due to a manufacturing capacity shortage). Typically, themanufacturer's customer would adjust its plans under the assumptionsthat their delivery would not be shipped until March 31^(st). However,sometimes the customer does not adjust its plans and rather prefers tosee if the manufacturer can do better in November. For the November run,it would be desirable to consider both the commit date of the demand(March 31^(st)) and the desired request date of the demand (say March1^(st)). Given the limited nature of assets and capacity throughout thesupply chain, the manufacturer should try to satisfy the demand by March1^(st) but attempt to guarantee satisfaction of the demand by its commitdate (March 31^(st)).

Conventional advanced planning systems require the demand to be enteredwith either March 1^(st) or March 31^(st) as the demand's target date.However, it is desirable to have a single planning method consider bothdates simultaneously with different priorities. So doing can lead to amore efficient allocation of assets and resources and substantiallyimproved customer service metrics. The present invention provides thissimultaneous date consideration within a linear programming basedadvanced planning system. However, it will be understood by thosepracticed in the art that the invention may also be applied to advancedplanning systems that are not based on linear programming (e.g.nonlinear programming, heuristics). Further, although presented below asan invention which considers two dates (request and commit), it shouldalso be understood that it is straightforward to extend the invention toconsider more than two dates.

Linear programming applications typically include the transformation ofinput files (block 100) into output files (block 108) through apre-processor (block 102), solver (block 104), and post-processor (block106) as shown in FIG. 1. The pre-processor (block 102) transforms theraw input files into a format useable by the linear programming solver.The solver (block 104) determines an optimal raw output solution whichis transformed by the post-processor (block 106) into a formatacceptable for usage. The present invention is embedded in the secondand fourth stages (blocks 102 and 106 respectively) and is used toachieve solutions based on consideration of multiple customer demanddates. Although the embodiment is described in a context where thesolver is a linear program, those skilled in the art will recognize thatany Advanced Planning System (APS) could be used as the solver includinga heuristic based APS.

Subsequent to solution generation, post-processing (block 106) iscompleted to strip out the artificial part numbers and thus presentcomprehensible output to the user. Compared with conventional systems,by simultaneously considering both request and commit dates for a singledemand, this invention provides a more efficient allocation of assetsand resources given the objective to provide excellent customer service.

FIG. 3 provides an illustration of the flow of the major steps describedbelow for each part number. FIG. 2 is a graphical illustration of theexample used to illustrate the method. Below is a summary of the salientsteps of the algorithm based on the example in FIG. 2. For each partnumber, P, for which we want to distinguish commit dates versus requestdates, execute the below items 301-306. In item 301 the inventioncreates a new part number, P-req, which will satisfy the requesteddemand. In item 302 create a new part number, P-com, which will satisfythe committed demand. In item 303 the invention assigns P's demand toP-req and P-com providing P-com with the commit date and P-req with therequest date. The priority of P-req's demand will be low and thepriority of P-com's demand will be slightly lower than the originalpriority. These priorities should be set so that the correspondingobjective function cost penalty of backordering the original demandpriority should be equal to the penalty of backordering the P-req demandplus the penalty of backordering the P-com demand. The total of thebackorder penalties is set equal to that of the original backorderpenalty because in the event of the LP not being able to satisfy thedemand by the commit date, the resulting backorder penalty should be thesame as that of any other demand with commit date of the same priority.In other words, once the business is unable to satisfy the demand by thecommit date, whether or not the customer requests or prefers it to bedelivered earlier doesn't really matter at this point. The penalty ofbackordering P-req demand is relatively low compared with the penalty ofbackordering P-com demand because satisfying the demand by the requestdate is not nearly as important as satisfying demands by their commitdates. Those skilled in the art will recognize that other backorderpenalty values could be used in lieu of those described in thispreferred embodiment. If any demands have request dates later thancommit dates, then the invention pushes the commit dates out to therequest dates.

In item 304, the invention creates binning records so that part P binsto parts P-req and P-com, each with 100%. This effectively doubles thesupply quantity, which balances the previous step's doubling of thedemand quantity. In item 305, the invention sets penalties for P-req andP-com as follows. The cost of shipping the artificial parts should beequal and total to be the same as the original cost of shipping part Pto its respective customer locations, and the processing cost of eachartificial part should be set to an arbitrary very low default value.The inventory cost of P-req should be set relatively high and for P-comset to zero. The relatively high inventory cost of P-req (at least ashigh as or very slightly higher than the original inventory cost of partP) discourages the early production and storage of P-req for which thereis no business purpose. The appropriateness of zero inventory cost forP-com is explained as follows. Suppose that the business is able todeliver P by the request date and, from the LP's viewpoint, ship thepart P-req at that time. This would result in inventory of part P-combetween the request date and the commit date (since the backorderequations prevent early shipments). This temporary inventory at P-com inthis situation is desirable because it allows the shipment on thecustomer's request date. This does not mean that there is inventory froma business standpoint but rather that there is inventory on theartificial P-com part which does not exist in the real world. Thoseskilled in the art will recognize that other penalty settings may bedesirable depending upon the business objectives and policies of theorganization using the invention.

In item 306, the invention updates other necessary input files (such asthe file of permissible shipments) and in item 307 the inventionexecutes linear programming engine. In item 308 the inventionpost-processes the output to strip out the artificial part numbers P-reqand P-com and re-institute the original part number P. The finalcustomer shipments for part P are set to the customer shipments forP-req. On a cumulative basis, the customer shipments from P-req willalways meet or exceed the customer shipments from P-com. Finally, outputa report indicating which DEM records were honored at an earlier datethan the commit date.

The invention includes an alternative method which can be used toachieve similar results through different methodology. In the alternatemethod a post-processing algorithm is used to sequentially modify the LPmodel, one demand record at a time, to determine if the demand recordcould be moved into an earlier date without substantially adjusting theproduction plan. In this method no adjustment is made to the datainputs, for example, binning or demand data. This alternative method isembedded within block 104 of FIG. 1.

More specifically, FIG. 4 illustrates the flow of the major items ofthis alternative method. In item 401, the invention solves an instanceof the model (where demand is initialized based on commit date) andmaintains the model and solution in memory for subsequentrecalculations. Next, in item 402, the invention introduces lower boundconstraints on all backorder (“B”) variables based on the current valueof the backorder variable. This introduction of lower bounds freezes thecurrent production plan with respect to customer shipments that havebeen satisfied in the current solution. Then, the invention sorts demandrecords from most to least important in the demand file DEM in item 403.

In item 404, for each record in DEM which has a request date earlierthan its commit date, the invention:

-   -   a) Finds the Backorder Constraint (BO) corresponding to the        current demand record and subtracts the demand quantity for the        current record from the right hand side of the BO constraint.        This is the first step in moving the current demand record to an        earlier date.    -   b) Removes lower bounds (introduced in Item 402) for all        Backorder variables corresponding to the PN, Customer, and        demand class associated with the current DEM record for        periods >=requested demand date and <commit date. This is done        to allow adjustments to BO constraints to be accommodated since        moving the current DEM record to an earlier date necessitates        adjustments to BO constraints.    -   c) Adds the demand quantity to the right hand side of the BO        constraints corresponding to the request date. This represents        the act of moving the current DEM record to the request date.    -   d) Updates the optimal solution to the LP model using the dual        simplex (prior art) method based on adjustments to the DEM        record and BO constraints in steps a-c.    -   e) Reintroduces lower bounds that were removed in sub-step (b),        where the new lower bound is set to the current value of the “B”        variables. In other words, the current solution (obtained        through steps a-e) is set as the new baseline.    -   f) Records the period(s) in which the demand was shipped to the        customer according to the updated optimal solution for reporting        in Item 405.

In item 405, the invention produces an output report indicating forwhich DEM records early shipping was achieved in order to betteraccommodate the requested demand date.

These two alternative methods described above (FIGS. 3 and 4) arerelated but have tradeoffs. For instance, the first method (FIG. 3) maybe somewhat more computationally demanding than the second methodbecause of resulting increases in model size due to the addition ofextra variables to model. On the other hand, the second method (FIG. 4)assumes “preemptive” priorities by choosing a specific sequence ofdemand records, whereas the first method (FIG. 3) allows forconsideration of all demand request and commit dates all at once whichcan be traded off against each other based on how model cost parametersare calibrated. Although the above methods are described in the contextof request and commit dates it will be understood by those practiced inthe art that the invention could be extended to consider more than twodates.

One way to extend the above concepts is illustrated in FIG. 5. Supposethat subsequent to the creation of an initial production plan usingnormal prices and costs, a customer indicates that it is interested inthe possibility of paying an additional fee in order to receive adelivery closer to the original request date. In block 500, the customerrequests more information from the supplier as to this possibility. Inblock 502, the supplier tentatively assumes that the customer will bewilling to pay more for the early delivery and increases the backorderpenalty relevant to that delivery. The amount of increase to thispenalty depends upon the additional price that the supplier will charge.It is possible to execute this method multiple times with variouspenalties associated with various price increases. The magnitude of theprice increase influences the manufacturing supplier's willingness togive this block 500 request a higher priority than its other demands.

In block 504, the linear programming equations are re-solved with thehigher backorder penalties. The resulting supply date (and correspondingprice increase) is presented in block 506 to the customer for itsconsideration. In block 508, the customer indicates whether or not it iswilling to pay for the earlier delivery date. If the customer is willingto pay the price, then the supplier will update its production planaccordingly. As implied earlier, this mechanism can be used multipletimes to provide the customer with multiple price and delivery timecombination alternatives.

A further extension would be to institute the concepts of FIG. 5proactively prior to an explicit (block 500) request from the customer.In this extension, the supplier does not wait for an explicit customerrequest, but rather acts as if the customer is already interested in thepossibility of earlier delivery at a premium price. In this instance,the supplier essentially executes the steps of FIG. 5 for each situationwhere the original request is not delivered when requested at normalpricing. Customers are then presented with alternative delivery datesand prices for their consideration.

The present invention could be implemented on an IBM P690 server usingthe AIX operating system. The steps for implementing the presentinvention are preferably programmed in C/C++. It should be understood bythose of ordinary skill in the art, however, that the representinvention is not limited to the above implementation and is independentof the computer/system architecture. Accordingly, the present inventionmay equally be implemented on other computing platforms, programminglanguages and operating systems, and also may be hardwired into acircuit or other computational component.

As shown above, the present invention provides the capability tosimultaneously consider both request and commit dates for at least onecustomer demand. In order to accomplish this, the invention introducestwo artificial part numbers for each part for which it is desirable todistinguish between request and commit dates. One artificial part willhave low priority demand with a target date set to the request date. Theother artificial part will have normal priority demand with a targetdate set to the commit date. Compared with conventional systems, bysimultaneously considering both request and commit dates for a singledemand, this invention provides a more efficient allocation of assetsand resources given the objective to provide excellent customer service.

While the invention has been described in terms of the preferredembodiments, those skilled in the art will recognize that the inventioncan be practiced with modification within the spirit and scope of theappended claims.

1. A method of production planning that considers multiple due dates forproviding the same resource to the same demand item, wherein saidmultiple due dates comprise a first date when said resource can beprovided to said demand item, and a later second date when said resourcemust be provided to said demand item, said method comprising: creating,from a single part number, a first part number associated with providingsaid resource to said demand item by said first date; creating, fromsaid single part number, a second part number associated with providingsaid resource to said demand item by said second date; performingproduction planning for both said first part number and said second partnumber to determine when said resource can be provided to said demanditem; and selecting one of said first part number and said second partnumber to satisfy said demand item.
 2. The method in claim 1, whereinsaid first part number has a different priority than said second partnumber.
 3. The method in claim 1, further comprising reporting to saiddemand item whether said resource will be supplied by said first date orsaid second date.
 4. The method in claim 1, further comprising creatingduplicate binning records to separately provide resources to supply saidfirst part number and said second part number.
 5. The method in claim 1,wherein said process of production planning simultaneously andseparately processes objective functions and constraints for said firstpart number from said second part number.
 6. The method in claim 1,wherein said second part number and said first part number compriseartificial part numbers that are based on said single part number. 7.The method in claim 1, wherein said process of production planningsimultaneously performs production planning for other resources andother demand items.
 8. A method of production planning that considersmultiple due dates for providing the same resource to the same demanditem, wherein said multiple due dates comprise a first date when saidresource can be provided to said demand item, and a later second datewhen said resource must be provided to said demand item, said methodcomprising: solving a production planning model based upon said firstdate to produce a first solution; re-solving said production planningmodel based upon said second date to produce a second solution; andoptimizing between said first solution and said second solution.
 9. Themethod of claim 8, wherein said re-solving processing is based oniterative solutions of a linear program.
 10. The method in claim 8,further comprising before re-solving said production planning model,sorting demand records in order of importance.
 11. The method in claim10, wherein said re-solving is performed on each demand item in thesorted order of importance.
 12. The method in claim 8, furthercomprising before re-solving said production planning model, changinglower bound constraints on backorder variables.
 13. The method in claim8, further comprising reporting the optimal solution produced duringsaid optimizing process.
 14. The method in claim 8, wherein saidre-solving process changes the required date for a single demand item,and wherein said re-solving process is repeated for all demand itemsthat have a first date that is before a corresponding second date.
 15. Aprogram storage device readable by machines, tangibly embodying aprogram of instructions executable by the machine to perform a method ofproduction planning that considers multiple due dates for providing thesame resource to the same demand item, wherein said multiple due datescomprise a first date when said resource can be provided to said demanditem, and a later second date when said resource must be provided tosaid demand item, said method comprising: creating, from a single partnumber, a first part number associated with providing said resource tosaid demand item by said first date; creating, from said single partnumber, a second part number associated with providing said resource tosaid demand item by said second date; performing production planning forboth said first part number and said second part number to determinewhen said resource can be provided to said demand item; and selectingone of said first part number and said second part number to satisfysaid demand item.
 16. The program storage device in claim 15, whereinsaid first part number has a different priority than said second partnumber.
 17. The program storage device in claim 15, wherein said methodfurther comprises reporting to said demand item whether said resourcewill be supplied by said first date or said second date.
 18. The programstorage device in claim 15, wherein said method further comprisescreating duplicate binning records to separately provide resources tosupply said first part number and said second part number.
 19. Theprogram storage device in claim 15, wherein said process of productionplanning simultaneously and separately processes objective functions andconstraints for said first part number from said second part number. 20.The program storage device in claim 15, wherein said second part numberand said first part number comprise artificial part numbers that arebased on said single part number.
 21. The program storage device inclaim 15, wherein said process of production planning simultaneouslyperforms production planning for other resources and other demand items.